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"""Implements to populate MongoDB collections with generated data used to calibrate Cost Model."""

from __future__ import annotations
from dataclasses import dataclass
from importlib.metadata import distribution
import time
import random
from typing import Sequence
import pymongo
from pymongo import InsertOne, IndexModel
from pymongo.collection import Collection
from random_generator import RandomDistribution
from common import timer_decorator
from config import DataGeneratorConfig, DataType
from database_instance import DatabaseInstance
from random_generator_config import distributions

__all__ = ['DataGenerator']


@dataclass
class FieldInfo:
    """Field-related information."""

    name: str
    type: DataType
    distribution: RandomDistribution


@dataclass
class CollectionInfo:
    """Collection-related information."""

    name: str
    fields: Sequence[FieldInfo]
    documents_count: int


class DataGenerator:
    """Create and populate collections with generated data."""

    def __init__(self, database: DatabaseInstance, config: DataGeneratorConfig):
        """Create new DataGenerator.

        Keyword Arguments:
        database -- Instance of Database object
        stringlength -- Length of generated strings
        """

        self.database = database
        self.config = config

        self.collection_infos = list(self._generate_collection_infos())

    def populate_collections(self) -> None:
        """Create and populate collections for each combination of size and data type in the corresponding 'docCounts' and 'dataTypes' input arrays.

        All collections have the same schema defined by one of the elements of 'collFields'.
        """

        if not self.config.enabled:
            return

        self.database.enable_cascades(False)
        t0 = time.time()
        for coll_info in self.collection_infos:
            coll = self.database.database.get_collection(coll_info.name)
            coll.drop()
            self._populate_collection(coll, coll_info)
            create_single_field_indexes(coll, coll_info.fields)
            create_compound_index(coll, coll_info.fields)

        t1 = time.time()
        print(f'\npopulate Collections took {t1-t0} s.')

    def _generate_collection_infos(self):
        for coll_template in self.config.collection_templates:
            fields = [
                FieldInfo(name=ft.name, type=ft.data_type,
                          distribution=distributions[ft.distribution])
                for ft in coll_template.fields
            ]
            for doc_count in self.config.collection_cardinalities:
                name = f'{coll_template.name}_{doc_count}'
                yield CollectionInfo(name=name, fields=fields, documents_count=doc_count)

    @timer_decorator
    def _populate_collection(self, coll: Collection, coll_info: CollectionInfo) -> None:
        print(f'\nGenerating ${coll_info.name} ...')
        batch_size = self.config.batch_size
        for _ in range(coll_info.documents_count // batch_size):
            populate_batch(coll, batch_size, coll_info.fields)
        if coll_info.documents_count % batch_size > 0:
            populate_batch(coll, coll_info.documents_count % batch_size, coll_info.fields)


def populate_batch(coll: Collection, documents_count: int, fields: Sequence[FieldInfo]) -> None:
    """Generate collection data and write it to the collection."""

    requests = [InsertOne(doc) for doc in generate_collection_data(documents_count, fields)]
    coll.bulk_write(requests, ordered=False)


def generate_collection_data(documents_count: int, fields: Sequence[FieldInfo]):
    """Generate random data for the specified fields of a collection."""

    documents = [{} for _ in range(documents_count)]
    for field in fields:
        for field_index, field_data in enumerate(field.distribution.generate(documents_count)):
            documents[field_index][field.name] = field_data
    return documents


def create_single_field_indexes(coll: Collection, fields: Sequence[FieldInfo]) -> None:
    """Create single-fields indexes on the given collection."""

    t0 = time.time()

    indexes = [IndexModel([(field.name, pymongo.ASCENDING)]) for field in fields]
    coll.create_indexes(indexes)

    t1 = time.time()
    print(f'createSingleFieldIndexes took {t1 - t0} s.')


def create_compound_index(coll: Collection, fields: Sequence[FieldInfo]) -> None:
    """Create a coumpound index on the given collection."""

    field_names = [fi.name for fi in fields if fi.type != DataType.ARRAY]
    if len(field_names) < 2:
        print(f'Collection: {coll.name} not suitable for compound index')
        return

    t0 = time.time()

    index_spec = [(field, pymongo.ASCENDING) for field in field_names]
    coll.create_index(index_spec)

    t1 = time.time()
    print(f'createCompoundIndex took {t1 - t0} s.')